The Inclusive Images Competition

19 citations recorded by the source corpus.

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A Step Toward More Inclusive People Annotations for Fairness (2021, background): “To partially address this limitation and encourage further research [2], Open Images now includes the Crowdsourced Extension1, containing new images from countries underrepresented in the original set.”
Multimodal datasets: misogyny, pornography, and malignant stereotypes (2021, background): “Various works [6, 7, 8, 9] have highlighted gender, racial, and geographical biases surrounding the sourcing of image datasets as well as the opacity of such endeavors [10].”
WILDS: A Benchmark of in-the-Wild Distribution Shifts (2020, positive): “…et al., 2020): for example, publicly available image datasets overrepresent images from the United States and Europe, producing drops in performance on images from the developing world (Shankar et al., 2017) and prompting creation of more geographically diverse image datasets (Atwood et al., 2020).”
Visual Classification via Description from Large Language Models (2022, methodology): “Inspired by the Inclusive Images Challenge (Atwood et al., 2020), we collected a challenge set consisting of images of weddings from various cultures to explore this bias.”
A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle (2019, background): “In other cases, it may be better to develop entirely new benchmarks that are more representative and better suited to the task at hand [2, 14, 27].”